A statistical research study that aimed to develop an empirical model for predicting the magnitude of the treatment effects on survival endpoints based on the treatment effects on pathological complete response (pCR) has been published in the Contemporary Clinical Trials.
The pCR rate can be assessed at the time of surgery in the neoadjuvant setting. Therefore, the US Food and Drug Administration (FDA) funded a meta-analysis of 12 international neoadjuvant trials in patients with early breast cancer (CTNeoBC; Cartazar et al. Lancet 2014) to evaluate pCR rate as a potential surrogate endpoint for prediction of long-term clinical benefit in breast cancer. The trial-level data from this analysis was used as a training data set to develop the statistical predictive model presented in the current study. The data from three other studies including GeparSixto was used to validate the new predictor. The model is able to predict the correlation between pCR and event-free survival as well as overall survival in patients with high risk early breast cancer.
Nekljudova V, Loibl S, von Minckwitz G, Schneeweiss A, Glück S, Crane R, Li H, Luo X.
Trial-level prediction of long-term outcome based on pathologic complete response (pCR) after neoadjuvant chemotherapy for early-stage breast cancer (EBC).
Contemp Clin Trials. 2018 71:194-198
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